In Julia, you can use the antijoin function from the DataFrames package to perform an anti-join operation on two dataframes.
An anti-join returns all rows from the first dataframe (the left dataframe) that do not have a match in the second dataframe (the right dataframe). The resulting dataframe will have the same number of columns as the left dataframe, and will only contain rows that do not have a match in the right dataframe.
Here is a visual representation of an anti-join using two dataframes df1 and df2:
df1 df2 +----+ +----+ | id | | id | +----+ +----+ | 1 | | 2 | | 2 | | 3 | | 3 | | 5 | | 4 | +----+ +----+ Result: +----+ | id | +----+ | 1 | +----+
Anti Join on DataFrames in Julia Examples
Here is an example of how to use the antijoin function:
using DataFrames # Define the left dataframe df1 = DataFrame(id = [1, 2, 3, 4], name = ["Alice", "Bob", "Charlie", "Dave"]) # Define the right dataframe df2 = DataFrame(id = [2, 3, 5], department = ["Sales", "Marketing", "Engineering"]) # Perform the anti-join result = antijoin(df1, df2, on = :id) # Print the resulting dataframe println(result)
The output of this code will be:
2×2 DataFrame
Row │ id name
│ Int64 String
─────┼───────────────
1 │ 1 Alice
2 │ 4 DaveIn this example, the antijoin function performs an anti-join on df1 and df2 using the id column as the join key. The resulting dataframe result contains all rows from df1 that do not have a matching id in df2, and only includes the id and name columns from df1.
You can also specify multiple columns as the join key by passing a vector of symbols to the on argument, like this:
result = antijoin(df1, df2, on = [:id, :name])
In this case, the anti-join will only return rows that do not have a matching value in both the id and name columns.
Here is another example of using the antijoin function to perform an anti-join on two dataframes:
using DataFrames # Define the left dataframe df1 = DataFrame(id = [1, 2, 3, 4], name = ["Alice", "Bob", "Charlie", "Dave"], department = ["Sales", "Marketing", "Engineering", "Human Resources"]) # Define the right dataframe df2 = DataFrame(id = [2, 3, 5], department = ["Sales", "Marketing", "Engineering"]) # Perform the anti-join result = antijoin(df1, df2, on = :department) # Print the resulting dataframe println(result)
The output of this code will be:
1×3 DataFrame
Row │ id name department
│ Int64 String String
─────┼────────────────────────────────
1 │ 4 Dave Human ResourcesIn this example, the antijoin function performs an anti-join on df1 and df2 using the department column as the join key. The resulting dataframe result contains all rows from df1 that do not have a matching department in df2, and includes all columns from df1.
You can also specify multiple columns as the join key by passing a vector of symbols to the on argument, like this:
result = antijoin(df1, df2, on = [:id, :department])
In this case, the anti-join will only return rows that do not have a matching value in both the id and department columns.
